# ParaQA: A Question Answering Dataset with Paraphrase Responses for Single-Turn Conversation

Source: [ParaQA: A Question Answering Dataset with Paraphrase Responses for Single-Turn Conversation](<https://www.sota2.com/research/paper/68fa697b1e209131cea22517>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T23:01:46.798Z

Authors: Endri Kacupaj, Barshana Banerjee, Kuldeep Singh, Jens Lehmann

Published: 2021-03-13T18:53:07.000Z

## Abstract

This paper presents ParaQA, a question answering (QA) dataset with multiple paraphrased responses for single-turn conversation over knowledge graphs (KG). The dataset was created using a semi-automated framework for generating diverse paraphrasing of the answers using techniques such as back-translation. The existing datasets for conversational question answering over KGs (single-turn/multi-turn) focus on question paraphrasing and provide only up to one answer verbalization. However, ParaQA contains 5000 question-answer pairs with a minimum of two and a maximum of eight unique paraphrased responses for each question. We complement the dataset with baseline models and illustrate the advantage of having multiple paraphrased answers through commonly used metrics such as BLEU and METEOR. The ParaQA dataset is publicly available on a persistent URI for broader usage and adaptation in the research community.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2103.07771>)

[PDF](<https://arxiv.org/pdf/2103.07771.pdf>)